Data Engineering on Microsoft Azure: Utilizing Multiple Languages in a Notebook | DP-203 Exam

Can Multiple Languages be Used in a Notebook? | DP-203 Exam

Question

When you create a notebook, you need to mention the pool either SQL or Spark Pool that needs to be connected to the notebook.

In terms of languages, a notebook needs to be set with a primary language.

Statement: It is possible to utilize multiple languages in one notebook.

Choose the correct option regarding the statement above.

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B.

Correct Answer: A

Here is the list of primary languages that are available within the notebook environment: PySpark (Python)

NET Spark (C#)

Spark (Scala)

Spark SQL.

It is possible to utilize multiple languages in one notebook by mentioning the language through a magic command at the beginning of a cell.

The magic commands for switching the cell languages are given as below:

Magic command Language Description

sbeepyspark Python meant Spore Conta
%%spark Scala against Spe st conten
ssa SparksQL againet Spark Contexts
eshesharp NET for Spark CH Execute a .NET for Spark C#

query against Spark Context.

It is not possible to reference variables or data directly across multiple languages in a Synapse Studio notebook.

To know more about creating, developing, and maintaining notebooks, please visit the below-given link:

The statement "It is possible to utilize multiple languages in one notebook" is true.

Azure Synapse Analytics allows you to create notebooks in which you can write code in different languages such as Python, R, Scala, SQL, and .NET languages. This feature enables data scientists, analysts, and engineers to collaborate effectively in a single environment.

Each notebook can be associated with a specific pool, either SQL or Spark, depending on the type of workload you want to run. The primary language of the notebook is set during the creation of the notebook and determines the default language of the code cells. However, you can add cells in different languages as needed by selecting the language from the drop-down menu.

For example, you can write a SQL query in one cell, then use Python or R in another cell to manipulate the query results, and then create a visualization using a plotting library in a third cell. This capability makes notebooks a powerful tool for data exploration, analysis, and visualization.

In summary, it is possible to utilize multiple languages in one notebook in Azure Synapse Analytics, and this feature enables data professionals to collaborate effectively and leverage the strengths of different languages for different tasks.